Research Scientist, Amazon Music - DISCO

About the position

Amazon Music is an immersive audio entertainment service that deepens

connections between fans, artists, and creators. From personalized music

playlists to exclusive podcasts, concert livestreams to artist merch, Amazon

Music is innovating at some of the most exciting intersections of music and

culture. We offer experiences that serve all listeners with our different tiers

of service: Prime members get access to all the music in shuffle mode, and top

ad-free podcasts, included with their membership; customers can upgrade to

Amazon Music Unlimited for unlimited, on-demand access to 100 million songs,

including millions in HD, Ultra HD, and spatial audio; and anyone can listen for

free by downloading the Amazon Music app or via Alexa-enabled devices. Join us

for the opportunity to influence how Amazon Music engages fans, artists, and

creators on a global scale.

We are seeking a highly skilled and analytical Research Scientist. You will play

an integral part in the measurement and optimization of Amazon Music marketing

activities. You will have the opportunity to work with a rich marketing dataset

together with the marketing managers. This role will focus on developing and

implementing causal models and randomized controlled trials to assess marketing

effectiveness and inform strategic decision-making. This role is suitable for

candidates with strong background in causal inference, statistical analysis, and

data-driven problem-solving, with the ability to translate complex data into

actionable insights. As a key member of our team, you will work closely with

cross-functional partners to optimize marketing strategies and drive business

growth.

Responsibilities

• Develop Causal Models

Design, build, and validate causal models to evaluate the impact of marketing

campaigns and initiatives. Leverage advanced statistical methods to identify and

quantify causal relationships.

• Conduct Randomized Controlled Trials

Design and implement randomized controlled trials (RCTs) to rigorously test the

effectiveness of marketing strategies. Ensure robust experimental design and

proper execution to derive credible insights.

• Statistical Analysis and Inference

Perform complex statistical analyses to interpret data from experiments and

observational studies. Use statistical software and programming languages to

analyze large datasets and extract meaningful patterns.

• Data-Driven Decision Making

Collaborate with marketing teams to provide data-driven recommendations that

enhance campaign performance and ROI. Present findings and insights to

stakeholders in a clear and actionable manner.

• Collaborative Problem Solving

Work closely with cross-functional teams, including marketing, product, and

engineering, to identify key business questions and develop analytical

solutions. Foster a culture of data-informed decision-making across the

organization.

• Stay Current with Industry Trends

Keep abreast of the latest developments in data science, causal inference, and

marketing analytics. Apply new methodologies and technologies to improve the

accuracy and efficiency of marketing measurement.

• Documentation and Reporting

Maintain comprehensive documentation of models, experiments, and analytical

processes. Prepare reports and presentations that effectively communicate

complex analyses to non-technical audiences.

Requirements

• PhD, or Master's degree and 4+ years of quantitative field research experience
• Experience investigating the feasibility of applying scientific principles and

concepts to business problems and products

• Experience analyzing both experimental and observational data sets
• Experience in causal modeling like graphical models, causal Bayesian network,

potential outcomes, A/B testing, experiments, quasi-experiments, and data

science workflows

Nice-to-haves

• Knowledge of R, MATLAB, Python or similar scripting language
• Experience with agile development
• Experience building web based dashboards using common frameworks
• Experience in machine learning, statistics, and deep learning
• Experience working with data mining on large datasets
• Experience working with cross-functional teams

Benefits

• health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health

Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy

Reimbursement coverage)

• 401(k) matching
• paid time off
• parental leave